In this paper, we focus on how the qualitative vocabulary of Dynalearn, which is used for describing dynamic systems, corresponds to the mathematical equations used in quantitative modeling. Then, we demonstrate the translation of a qualitative model into a quantitative model, using the example of an object falling with air resistance.
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A kinetic model for the formation of acrylamide in a fructose-asparagine reaction system at initial pH 5.5 is proposed, based on an approach called multiresponse kinetic modelling. The formation of acetic acid and formic acid from the degradation of fructose and its isomer glucose was included in the proposed kinetic model. The kinetic model suggests that the effect of temperature on acrylamide formation with fructose is more due to the preceding steps with the formation of the Schiff base. The use of fructose and lower pH resulted in a higher yield of acrylamide (3%), suggesting that both can play an important role in acrylamide mitigation. Furthermore, these models have shown that, at high temperatures (120-200 °C), the Maillard reaction rapidly goes into the advanced stages, forming high amounts of organic acids and high molecular weight melanoidins. Overall, these mechanistic models provide more insight of the formation of acrylamide in a quantitative way.
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Art therapy is widely used and effective in the treatment of patients diagnosed with Personality Disorders (PDs). Current psychotherapeutic approaches may benefit from this additional therapy to improve their efficacy. But what is the patient perspective upon this therapy? This study explored perceived benefits of art therapy for patients with PDs to let the valuable perspective of patients be taken into account. Using a quantitative survey study over 3 months (N = 528), GLM repeated measures and overall hierarchical regression analyses showed that the majority of the patients reported quite a lot of benefit from art therapy (mean 3.70 on a 5-point Likert scale), primarily in emotional and social functioning. The improvements are concentrated in specific target goals of which the five highest scoring goals affected were: expression of emotions, improved (more stable/positive) self-image, making own choices/autonomy, recognition of, insight in, and changing of personal patterns of feelings, behaviors and thoughts and dealing with own limitations and/or vulnerability. Patients made it clear that they perceived these target areas as having been affected by art therapy and said so at both moments in time, with a higher score after 3 months. The extent of the perceived benefits is highly dependent for patients on factors such as a non-judgmental attitude on the part of the therapist, feeling that they are taken seriously, being given sufficient freedom of expression but at the same time being offered sufficient structure and an adequate basis. Age, gender, and diagnosis cluster did not predict the magnitude of perceived benefits. Art therapy provides equal advantages to a broad target group, and so this form of therapy can be broadly indicated. The experienced benefits and the increase over time was primarily associated with the degree to which patients perceive that they can give meaningful expression to feelings in their artwork. This provides an indication for the extent of the benefits a person can experience and can also serve as a clear guiding principle for interventions by the art therapist.
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The main goal of this study was to investigate if a computational analyses of text data from the National Student Survey (NSS) can add value to the existing, manual analysis. The results showed the computational analysis of the texts from the open questions of the NSS contain information which enriches the results of standard quantitative analysis of the NSS.
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Industrial Symbiosis Networks (ISNs) consist of firms that exchange residual materials and energy locally, in order to gain economic, environmental and/or social advantages. In practice, ISNs regularly fail when partners leave and the recovery of residual streams ends. Regarding the current societal need for a shift towards sustainability, it is undesirable that ISNs should fail. Failures of ISNs may be caused by actor behaviour that leads to unanticipated economic losses. In this paper, we explore the effect of these behaviours on ISN robustness by using an agent-based model (ABM). The constructed model is based on insights from both literature and participatory modelling in three real-world cases. It simulates the implementation of synergies for local waste exchange and compost production. The Theory of Planned Behaviour (TPB) was used to model agent behaviour in time-dependent bilateral negotiations and synergy evaluation processes. We explored model behaviour with and without TPB logic across a range of possible TPB input variables. The simulation results show how the modelled planned behaviour affects the cash flow outcomes of the social agents and the robustness of the network. The study contributes to the theoretical development of industrial symbiosis research by providing a quantitative model of all ISN implementation stages, in which various behavioural patterns of entrepreneurs are included. It also contributes to practice by offering insights on how network dynamics and robustness outcomes are not only related to context and ISN design, but also to actor behaviour.
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The goal of this study was therefore to test the idea that computationally analysing the Fontys National Student Surveys (NSS) open answers using a selection of standard text mining methods (Manning & Schütze 1999) will increase the value of these answers for educational quality assurance. It is expected that human effort and time of analysis will decrease significally. The text data (in Dutch) of several years of Fontys National Student Surveys (2013-2018) was provided to Fontys students of the minor Applied Data Science. The results of the analysis were to include topic and sentiment modelling across multiple years of survey data. Comparing multiple years was necessary to capture and visualize any trends that a human investigator may have missed while analysing the data by hand. During data cleaning all stop words and punctuation were removed, all text was brought to a lower case, names and inappropriate language – such as swear words – were deleted. About 80% of 24.000 records were manually labelled with sentiment; reminder was used for algorithms’ validation. In the following step a machine learning analysis steps: training, testing, outcomes analysis and visualisation, for a better text comprehension, were executed. Students aimed to improve classification accuracy by applying multiple sentiment analysis algorithms and topics modelling methods. The models were chosen arbitrarily, with a preference for a low complexity of a model. For reproducibility of our study open source tooling was used. One of these tools was based on Latent Dirichlet allocation (LDA). LDA is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar (Blei, Ng & Jordan, 2003). For topic modelling the Gensim (Řehůřek, 2011) method was used. Gensim is an open-source vector space modelling and topic modelling toolkit implemented in Python. In addition, we recognized the absence of pretrained models for Dutch language. To complete our prototype a simple user interface was created in Python. This final step integrated our automated text analysis with visualisations of sentiments and topics. Remarkably, all extracted topics are related to themes defined by the NSS. This indicates that in general students’ answers are related to topics of interest for educational institutions. The extracted list of the words related to the topic is also relevant to this topic. Despite the fact that most of the results require further human expert interpretation, it is indicative to conclude that the computational analysis of the texts from the open questions of the NSS contain information which enriches the results of standard quantitative analysis of the NSS.
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Pressure on natural resources, unsustainable production and consumption, inequality and a growing global population lie at the base of the big challenges that people face. This chapter investigates how businesses can take responsibility in dealing with these challenges by means of frugal business model innovation. The notion of ‘frugal innovation’ was first introduced in the context of emerging markets, giving non-affluent customers opportunities to consume affordable products and services suited to their needs. Business modelling with a frugal mindset opens up a path that provides significant value while minimizing the use of resources such as energy, capital and time. Business models require intentional design if they are to deliver aspired sustainability impacts. Diminish or simplify resources can be described as the means to remove or reduce features, resources, required activities and/or waste streams. Decompose can be described as the removal of resources from the commercial value proposition and replacing them with resources the user/consumer already can access or uses. This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in Circular Economy : Challenges and Opportunities for Ethical and Sustainable Business on 2021, available online: https://doi.org/10.4324/9780367816650
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In this mixed methods study, a moderated mediation model predicting effects of leader-member exchange (LMX) and organizational citizenship behaviors (OCB) on innovative work behaviors, with employability as a mediator, has been tested. Multi-source data from 487 pairs of employees and supervisors working in 151 small and medium-sized enterprises (SMEs) supported our hypothesized model. The results of structural equation modelling provide support for our model. In particular, the benefits of close relationships and high-quality exchanges between employee and supervisor (LMX), and fostering individual development as a result of employees’ OCB have an indirect effect on innovative work behaviors through positive effects on workers’ employability. Innovative work behaviors depend on employees’ knowledge, skills, and expertise. In other words, enhancing workers’ employability nurtures innovative work behaviors. In addition, we found a moderation effect of organizational politics on the relationship between employability and innovative work behaviors. Secondly, qualitative methods focusing on experiences of the antecedents and outcomes of employability were used to complement our quantitative results. All in all, this study has important consequences for managerial strategies and practices in SMEs and call for an awareness of the dysfunctional effect of perceived organizational politics.
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BACKGROUND: The number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps.OBJECTIVE: This study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app.METHODS: A quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed.RESULTS: The multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed.CONCLUSIONS: This study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.
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Simulation transparency is becoming more crucial in the decision making process when quantitative computer tools are used to justify some strategies.
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